Interleaver Optimization using Population-Based Metaheuristics

0350889 - ÚI 2011 RIV CZ eng J - Článek v odborném periodiku
Snášel, V. - Platoš, J. - Krömer, P. - Abraham, A. - Ouddane, N. - Húsek, Dušan
Interleaver Optimization using Population-Based Metaheuristics.
Neural Network World. Roč. 20, č. 5 (2010), s. 591-608. ISSN 1210-0552
Grant CEP: GA ČR GA205/09/1079
Grant ostatní: GA ČR(CZ) GA102/09/1494
Výzkumný záměr: CEZ:AV0Z10300504
Klíčová slova: turbo codes * global optimization * genetic algorithms * differential evolution * noisy communication channel
Kód oboru RIV: IN - Informatika
Impakt faktor: 0.511, rok: 2010

Since their appearance in 1993, first approaching the Shannon limit, turbo codes have given a new direction in the channel encoding field, especially since they have been adopted for multiple norms of telecommunications such as deeper communication. A robust interleaver can significantly contribute to the overall performance a turbo code system. Search for a good interleaver is a complex combinatorial optimization problem. In this paper, we present genetic algorithms and differential evolution, two bio-inspired approaches that have proven the ability to solve non-trivial combinatorial optimization tasks, as promising optimization methods to find a well-performing interleaver for large frame sizes.
Trvalý link: http://hdl.handle.net/11104/0006150